Parallel symbolic state-space exploration is difficult, but what is the alternative?

State-space exploration is an essential step in many modeling and analysis problems. Its goal is to find the states reachable from the initial state of a discrete-state model described. The state space can used to answer important questions, e.g., "Is there a dead state?" and "Can N become negative?", or as a starting point for sophisticated investigations expressed in temporal logic. Unfortunately, the state space is often so large that ordinary explicit data structures and sequential algorithms cannot cope, prompting the exploration of (1) parallel approaches using multiple processors, from simple workstation networks to shared-memory supercomputers, to satisfy large memory and runtime requirements and (2) symbolic approaches using decision diagrams to encode the large structured sets and relations manipulated during state-space generation. Both approaches have merits and limitations. Parallel explicit state-space generation is challenging, but almost linear speedup can be achieved; however, the analysis is ultimately limited by the memory and processors available. Symbolic methods are a heuristic that can efficiently encode many, but not all, functions over a structured and exponentially large domain; here the pitfalls are subtler: their performance varies widely depending on the class of decision diagram chosen, the state variable order, and obscure algorithmic parameters. As symbolic approaches are often much more efficient than explicit ones for many practical models, we argue for the need to parallelize symbolic state-space generation algorithms, so that we can realize the advantage of both approaches. This is a challenging endeavor, as the most efficient symbolic algorithm, Saturation, is inherently sequential. We conclude by discussing challenges, efforts, and promising directions toward this goal

Free-breathing black-blood CINE fast-spin echo imaging for measuring abdominal aortic wall distensibility: a feasibility study.

The paper reports a free-breathing black-blood CINE fast-spin echo (FSE) technique for measuring abdominal aortic wall motion. The free-breathing CINE FSE includes the following MR techniques: (1) variable-density sampling with fast iterative reconstruction; (2) inner-volume imaging; and (3) a blood-suppression preparation pulse. The proposed technique was evaluated in eight healthy subjects. The inner-volume imaging significantly reduced the intraluminal artifacts of respiratory motion (p  =  0.015). The quantitative measurements were a diameter of 16.3  ±  2.8 mm and wall distensibility of 2.0  ±  0.4 mm (12.5  ±  3.4%) and 0.7  ±  0.3 mm (4.1  ±  1.0%) for the anterior and posterior walls, respectively. The cyclic cross-sectional distensibility was 35  ±  15% greater in the systolic phase than in the diastolic phase. In conclusion, we developed a feasible CINE FSE method to measure the motion of the abdominal aortic wall, which will enable clinical scientists to study the elasticity of the abdominal aorta

A structural and physical study of sol–gel methacrylate–silica hybrids: intermolecular spacing dictates the mechanical properties

Sol–gel hybrids are inorganic/organic co-networks with nanoscale interactions between the components leading to unique synergistic mechanical properties, which can be tailored, via a selection of the organic moiety. Methacrylate based polymers present several benefits for class II hybrids (which exhibit formal covalent bonding between the networks) as they introduce great versatility and can be designed with a variety of chemical side-groups, structures and morphologies. In this study, the effect of high cross-linking density polymers on the structure–property relationships of hybrids generated using poly(3-trimethoxysilylpropyl methacrylate) (pTMSPMA) and tetraethyl orthosilicate (TEOS) was investigated. The complexity and fine scale of the co-network interactions requires the development of new analytical methods to understand how network evolution dictates the wide-ranging mechanical properties. Within this work we developed data manipulation techniques of acoustic-AFM and solid state NMR output that provide new approaches to understand the influence of the network structure on the macroscopic elasticity. The concentration of pTMSPMA in the silica sol affected the gelation time, ranging from 2 h for a hybrid made with 75 wt% inorganic with pTMSPMA at 2.5 kDa, to 1 minute for pTMSPMA with molecular weight of 30 kDa without any TEOS. A new mechanism of gelation was proposed based on the different morphologies derived by AC-AFM observations. We established that the volumetric density of bridging oxygen bonds is an important parameter in structure/property relationships in SiO2 hybrids and developed a method for determining it from solid state NMR data. The variation in the elasticity of pTMSPMA/SiO2 hybrids originated from pTMSPMA acting as a molecular spacer, thus decreasing the volumetric density of bridging oxygen bonds as the inorganic to organic ratio decreased

Bino Dark Matter and Big Bang Nucleosynthesis in the Constrained E6SSM with Massless Inert Singlinos

We discuss a new variant of the E6 inspired supersymmetric standard model (E6SSM) in which the two inert singlinos are exactly massless and the dark matter candidate has a dominant bino component. A successful relic density is achieved via a novel mechanism in which the bino scatters inelastically into heavier inert Higgsinos during the time of thermal freeze-out. The two massless inert singlinos contribute to the effective number of neutrino species at the time of Big Bang Nucleosynthesis, where the precise contribution depends on the mass of the Z' which keeps them in equilibrium. For example for mZ' > 1300 GeV we find Neff \approx 3.2, where the smallness of the additional contribution is due to entropy dilution. We study a few benchmark points in the constrained E6SSM with massless inert singlinos to illustrate this new scenario.Comment: 24 pages, revised for publication in JHE

Exploring an informed decision-making framework using in-home sensors: older adults’ perceptions

Background Sensor technologies are designed to assist independent living of older adults. However, it is often difficult for older adults to make an informed decision about adopting sensor technologies.Objective To explore Bruce’s framework of informed decision making (IDM) for in-home use of sensor technologies in community-dwelling elders.Method The IDM framework guided development of a semi-structured interview. A theory-driven coding approach was used for analysis.Results Participants supported most of the elements of the framework, but not all aspects of each element were addressed. Perceived usefulness of technologies was identified as an area for framework extension.Conclusion This paper provides useful information for health care professionals to consider how to enhance IDM of older adults regarding the use of sensor technologies. The results also illuminate elements of the IDM framework that may be critical to facilitating independent living for older adults

Fingertip‐skin‐inspired highly sensitive and multifunctional sensor with hierarchically structured conductive graphite/polydimethylsiloxane foams

Fingertip skin exhibits high sensitivity in a broad pressure range, and can detect diverse stimuli, including textures, temperature, humidity, etc. Despite adopting diverse microstructures and functional materials, achieving skin sensor devices possessing high pressure sensitivity over a wide linear range and with multifunctional sensing capabilities is still challenging. Herein, inspired by the microstructures of fingertip skin, a highly sensitive skin sensor is demonstrated with a linear response over a broad pressure range and multifunctional sensing capabilities. The porous sensing layer is designed with hierarchical microstructures on the surface. By optimizing the porosity and the graphite concentration, a fabricated skin sensor device exhibits a superior sensitivity of 245 kPa−1 over a broad linear pressure range from 5 Pa to 120 kPa. For practical application demonstrations, the sensor devices are utilized to monitor subtle wrist pulse and diverse human motions including finger bending, wrist bending, and feet movement. Furthermore, this novel sensor device demonstrates potential applications in recognizing textures and detecting environmental temperatures, thereby marking an important progress for constructing advanced electronic skin